A Scheduling Toolkit for Multiprocessor-Task Programming with Dependencies

摘要

The performance of many scientific applications for distributed memory platforms can be increased by utilizing multiprocessor-task programming. To obtain the minimum parallel runtime an appropriate schedule that takes the computation and communication performance of the target platform into account is required. However, many tools and environments for multiprocessor-task programming lack the support for an integrated scheduler. This paper presents a scheduling toolkit, which provides this support and integrates popular scheduling algorithms. The implemented scheduling algorithms provide an infrastructure to automatically determine a schedule for multiprocessor-tasks with dependencies represented by a task graph.